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Evaluation of ACR-TIRADS Classification System in Risk Stratification of Thyroid Nodules: A Prospective Observational Study

Research output: Contribution to journalArticlepeer-review

Abstract

Aim: To determine the sensitivity and specificity of ACR-TIRADS with final histopathology report, evaluate the diagnostic accuracy of USG-guided FNAC with final histopathology report, and determine the concordance between ACR-TIRADS score and Bethesda classification of FNAC. Material and Methods: This prospective observational study was conducted in the Department of General Surgery, Kasturba Medical College, Manipal, from March 2019 to August 2020. Forty-eight patients admitted for thyroid surgeries with available ACR-TIRADS and Bethesda FNAC reports were included. Clinical data, imaging findings, and cytology reports were collected and correlated with final histopathological findings. Statistical analysis was performed to determine sensitivity, specificity, and diagnostic accuracy. Results: Among 48 patients, 87.5% were females with mean age 31-60 years. According to ACR-TIRADS classification, 37.5% were TR4 (moderately suspicious), 35% were TR3 (mildly suspicious), 22% were TR2 (not suspicious), and 4% were TR5 (highly suspicious). FNAC revealed 52% benign (Bethesda II), 14% suspicious for malignancy (Bethesda V), and 4% malignant (Bethesda VI) lesions. Final histopathology confirmed malignancy in 33% cases. ACR-TIRADS demonstrated high sensitivity (81.25%) and specificity (78.12%) with overall diagnostic accuracy of 79.17%. FNAC demonstrated sensitivity of 75% and specificity of 78.57%. Moderate agreement was noted between ACR-TIRADS and Bethesda classification (kappa = 0.45). Conclusion: The American College of Radiology TI-RADS demonstrates excellent discriminatory capability for thyroid malignancy risk assessment using sonographic characteristics. Initial screening with USG and ACR-TIRADS scoring helps identify benign lesions and reduces unnecessary biopsies while appropriately triaging suspicious lesions for FNAC.

Original languageEnglish
Pages (from-to)630-636
Number of pages7
JournalInternational Journal of Drug Delivery Technology
Volume16
Issue number2
DOIs
Publication statusPublished - 2026

All Science Journal Classification (ASJC) codes

  • Pharmaceutical Science

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